Design and implementation of intelligent assistance system for emergency rescue of critical care ambulance

Abstract: The emergency assistance system is based on the EC5-1719CLDNA high-performance single-board computer, with the addition of human vital signs monitoring sensors, audio and video modules, wireless transmission modules, databases and application software, as well as ECG monitoring equipment, to achieve real-time collection and monitoring of human vital signs, medical history collection, rapid diagnosis of illness, suspected case query, remote expert emergency, ECG analysis and other functions. This system is used to quickly diagnose patients' illnesses and guide emergency treatment in the pre-hospital emergency stage, effectively reducing the mortality and disability rates of patients.

0 Introduction

There is a "time window" for emergency treatment for accidents, sudden illnesses and other diseases. If a quick diagnosis and effective emergency treatment can be given in the pre-hospital emergency stage, the mortality and disability rates can be reduced to a great extent. However, due to objective conditions, it is difficult for the mobile medical team on the medical ambulance to be equipped with experienced specialists, so the most timely and effective measures are not taken, or the best time for rescue is missed [1].

In response to the above problems, this paper uses EC5-1719CLDNA (Embedded Star) as the system kernel, combined with human vital signs monitoring sensors, audio and video modules, TD-SCDMA wireless transmission modules, and GPS modules to implement an ambulance emergency intelligent assistance system that provides an effective solution.

1 System Design and Implementation

The system consists of two parts: the ambulance end and the emergency center end. The two sides communicate data through the TD-SCDMA wireless module. The ambulance end mainly completes the collection of the patient's physiological characteristics (body temperature, pulse, respiration, blood pressure), the analysis of the patient's electrocardiogram, and transmits the collected data to the emergency center end through the wireless module in real time, so as to facilitate the center to make a comprehensive remote diagnosis of the patient.

The emergency center is responsible for managing and deploying ambulances, receiving real-time vital signs data and preliminary diagnosis results sent by each ambulance, and providing data, images and other diagnostic references to emergency center experts through real-time audio and video communications to guide the ambulance to implement more effective treatment plans.

The overall block diagram of the whole system is shown in Figure 1.

Figure 1 Overall framework of the critical care ambulance assistance system

The ambulance uses EC5-1719CLDNA (Embedded Star) high-performance single-board computer, and uses integrated sensors to collect, process and transmit pulse, body temperature and respiratory signals in real time. The design block diagram is shown in Figure 2.

Figure 2: Ambulance-side functional system structure

The entire ambulance end can be divided into four modules: a data collection module that completes the collection of patient physiological characteristics; a human-computer interaction module that completes the display of patient data analysis results; a wireless module that completes communication with the center; and a sound and image processing module that completes video conversations with the center.

The data acquisition module is the key part of the whole system. The collected signal is realized by the 16-bit ∑-Δ analog/digital converter AD7705. The chip contains a digital filter, so a separate filter circuit is omitted and a good filtering effect is achieved. The control adopted is controlled by two single-chip microcomputers, and the collected signal is sent to the main control system for analysis and processing.

Since the ambulance in this system interacts with the central end while moving, a wireless network card is configured at the central end to receive data from the ambulance terminal. In addition, this system also uses a GPS module from Coret (with a nominal positioning accuracy of 10 m) at the ambulance terminal. The local GPS coordinates are obtained from the satellite through the GPS terminal, and the positioning information is used to help the ambulance end and the emergency center end understand the current location of the ambulance.

Similarly, transmitting audio and video in motion also puts forward higher requirements than in stillness. This system adopts socket technology to transmit audio and video data wirelessly. At the same time, in order to alleviate the data backlog caused by poor network communication and the situation where data cannot be sent out, the system sending end adopts a stop-and-wait strategy, that is, it monitors the receiving end after each data is sent and sets a flag to determine whether to stop compressing the video frame. At the receiving end, after receiving the video frame, the flag is sent to the sending end to make the receiving end start compression and transmit the next frame of data. In this way, when the network is abnormal, due to stopping compression, there will be no data backlog.

2 System Testing

2.1 Pulse module test

For the same person, the waveform of the pulse sensor HK-2000B signal is measured by an oscilloscope and compared with the output waveform of this system. The waveforms are shown in Figure 3 and Figure 4.

Figure 3 Oscilloscope output pulse waveform

Figure 4 Output waveform of this system

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The results of pulse measurement for subjects of different ages, genders and conditions are different.

Test conclusion: By comparing with the conventional pulse measurement method, it is found that the system measures pulse more accurately and is easier to store and process.

2.2 Breathing module test

For the same person, the waveform of the HXH-2 respiratory wave sensor signal was measured with an oscilloscope and compared with the output waveform of this system. The waveforms are shown in Figure 5 and Figure 6.

Figure 5 Oscilloscope output breathing waveform

Figure 6 Output waveform of this system

Test conclusion: The test waveform is the same as the oscilloscope output waveform, and the interference is well removed through filtering. Through the measurement of different people, it is found that the breathing frequency is consistent with the medical theoretical value.

2.3 Temperature and blood pressure module test

For different subjects, measurements were performed using a standard thermometer and this system respectively. Some of the measurement data are shown in Table 1.

Table 1 Partial measurement data

Test conclusion: The temperature of multiple subjects was tested and compared under different conditions using a thermometer and the temperature measurement module of the system. Due to errors in the electronic components themselves and interference from the circuit itself, there were certain errors in the measurement results, but since the errors were very small, the measurement results can be used for medical diagnosis.

Blood pressure was measured for subjects of different ages, genders and conditions, as shown in Table 2.

Table 2 Measurement results

Test conclusion: The blood pressure tests of multiple subjects were conducted under different conditions using a conventional sphygmomanometer and the blood pressure measurement module of this system, and the results were basically consistent.

2.4 ECG module test

The data is obtained through the electrocardiograph and stored in the database, and then the twelve-lead waveform, data processing results and disease diagnosis results are obtained from the display interface. The experiment selects a normal young man in his twenties for electrocardiograph detection, taking the first lead as an example:

The waveform and diagnosis result corresponding to the first lead are shown in FIG7 .

Figure 7 ECG test diagnosis results

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Functions of this software: It can display 12-lead ECG waveforms simultaneously, and process all 12-lead waveform data. By selecting and opening different windows, you can observe the diagnosis results, data processing results, etc. The overall interface of real-time monitoring is shown in Figure 8.

FIG. 8 is a diagram showing the overall measurement results of a certain subject.

Figure 8 Real-time monitoring interface

3 Conclusion

The critical care ambulance emergency intelligent assistance system is a system centered on emergency care, integrating real-time monitoring, disease diagnosis, telemedicine and other functions. The system is based on emergency care and integrates wireless networks, databases, sensors, audio and video, GPS and other technologies. It has powerful functions and good stability, and provides effective protection for reducing patient mortality and disability rates, and has high practical value.

On this basis, the system can be further improved and expanded. For example, the function of recording and analyzing physiological parameter data can be added to the emergency center, and electroencephalogram analysis can also be added to form a comprehensive medical monitoring and diagnosis assistance system. In addition, the emergency center can be designed as an expert network, so that experts can make remote diagnosis without geographical restrictions.

The design of this system also has great scalability in the application field. For example, it can be designed as a portable device for use in special environments such as outdoor exploration. Therefore, it has broad application prospects.

References

[1] Zhou Jiru. Practical Emergency First Aid[M]. Beijing: Science and Technology Literature Press, 2006.

[2] Ouyang Qin. Clinical Diagnosis[M]. Beijing: People's Medical Publishing House, 2005.

[3] Huang Daxian. Modern Electrocardiography[M]. Beijing: People's Military Medical Publishing House, 1997.

[4] Mao Zhicheng. Medical Rescuer[M]. Beijing: Peking Union Medical College Press, 2007.

[5] Qiushi Technology. Visual C++ Audio and Video Coding and Decoding Technology and Practice[M]. Beijing: Posts and Telecommunications Press, 2006.

[6] Wu Zhijun, Ma Lan, Shen Xiaoyun. Visual C++ Video Conference Development Technology and Examples [M]. Beijing: People's Posts and Telecommunications Press, 2006.
[7] [US] Vikram Vaswani. MySQL Complete Manual [M]. Translated by Xu Xiaoqing. Beijing: Electronic Industry Press, 2004.